The clinical value of inflammation index in predicting ICU mortality of critically ill patients with intracerebral hemorrhage.

The inflammatory response holds paramount significance in the context of intracerebral hemorrhage (ICH) and exhibits a robust correlation with mortality rates. Biological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) play crucial roles in influencing the systemic inflammatory response following ICH. This study aims to compare the predictive efficacy of NLR, PLR, LMR, SII, and SIRI concerning the risk of mortality in the intensive care unit (ICU) among critically ill patients with ICH. Such a comparison seeks to elucidate their early warning capabilities in the management and treatment of ICH. Patients with severe ICH requiring admission to the ICU were screened from the Medical Information Marketplace for Intensive Care (MIMIC-IV) database. The outcomes studied included ICU mortality and 30 day ICU hospitalization rates, based on tertiles of the NLR index level. To explore the relationship between the NLR index and clinical outcomes in critically ill patients with ICH, we utilized receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and multivariate logistic regression analysis. A total of 869 patients (51.9% male) were included in the study, with an ICU mortality rate of 22.9% and a 30 day ICU hospitalization rate of 98.4%. Among the five indicators examined, both the ROC curve and DCA indicated that NLR (AUC: 0.660, 95%CI: 0.617-0.703) had the highest predictive ability for ICU mortality. Moreover, this association remained significant even after adjusting for other confounding factors during multivariate analysis (HR: 3.520, 95%CI: 2.039-6.077). Based on the results of the multivariate analysis, incorporating age, albumin, lactic acid, NLR, and GCS score as variables, we developed a nomogram to predict ICU mortality in critically ill patients with ICH. NLR emerges as the most effective predictor of ICU mortality risk among critically ill patients grappling with ICH when compared to the other four indicators. Furthermore, the integration of albumin and lactic acid indicators into the NLR nomogram enhances the ability to promptly identify ICU mortality in individuals facing severe ICH.

Zhao G ，Gu Y ，Wang Z ，Chen Y ，Xia X ... -  《Frontiers in Public Health》

The clinical value of neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR) and systemic inflammation response index (SIRI) for predicting the occurrence and severity of pneumonia in patients wi

Inflammatory mechanisms play important roles in intracerebral hemorrhage (ICH) and have been linked to the development of stroke-associated pneumonia (SAP). The neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR) and systemic inflammation response index (SIRI) are inflammatory indexes that influence systemic inflammatory responses after stroke. In this study, we aimed to compare the predictive value of the NLR, SII, SIRI and PLR for SAP in patients with ICH to determine their application potential in the early identification of the severity of pneumonia. Patients with ICH in four hospitals were prospectively enrolled. SAP was defined according to the modified Centers for Disease Control and Prevention criteria. Data on the NLR, SII, SIRI and PLR were collected at admission, and the correlation between these factors and the clinical pulmonary infection score (CPIS) was assessed through Spearman's analysis. A total of 320 patients were enrolled in this study, among whom 126 (39.4%) developed SAP. The results of the receiver operating characteristic (ROC) analysis revealed that the NLR had the best predictive value for SAP (AUC: 0.748, 95% CI: 0.695-0.801), and this outcome remained significant after adjusting for other confounders in multivariable analysis (RR=1.090, 95% CI: 1.029-1.155). Among the four indexes, Spearman's analysis showed that the NLR was the most highly correlated with the CPIS (r=0.537, 95% CI: 0.395-0.654). The NLR could effectively predict ICU admission (AUC: 0.732, 95% CI: 0.671-0.786), and this finding remained significant in the multivariable analysis (RR=1.049, 95% CI: 1.009-1.089, P=0.036). Nomograms were created to predict the probability of SAP occurrence and ICU admission. Furthermore, the NLR could predict a good outcome at discharge (AUC: 0.761, 95% CI: 0.707-0.8147). Among the four indexes, the NLR was the best predictor for SAP occurrence and a poor outcome at discharge in ICH patients. It can therefore be used for the early identification of severe SAP and to predict ICU admission.

Wang RH ，Wen WX ，Jiang ZP ，Du ZP ，Ma ZH ，Lu AL ，Li HP ，Yuan F ，Wu SB ，Guo JW ，Cai YF ，Huang Y ，Wang LX ，Lu HJ ... -  《Frontiers in Immunology》

The clinical value of nutritional and inflammatory indicators in predicting pneumonia among patients with intracerebral hemorrhage.

Immunosuppression and malnutrition play pivotal roles in the complications of intracerebral hemorrhage (ICH) and are intricately linked to the development of stroke-associated pneumonia (SAP). Inflammatory markers, including NLR (neutrophil-to-lymphocyte ratio), SII (systemic immune inflammation index), SIRI (systemic inflammatory response index), and SIS (systemic inflammation score), along with nutritional indexes such as CONUT (controlling nutritional status) and PNI (prognostic nutritional index), are crucial indicators influencing the inflammatory state following ICH. In this study, our objective was to compare the predictive efficacy of inflammatory and nutritional indices for SAP in ICH patients, aiming to determine and explore their clinical utility in early pneumonia detection. Patients with severe ICH requiring ICU admission were screened from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The outcomes included the occurrence of SAP and in-hospital death. Receiver operating characteristic (ROC) analysis, multivariate logistic regression, smooth curve analysis, and stratified analysis were employed to investigate the relationship between the CONUT index and the clinical outcomes of patients with severe ICH. A total of 348 patients were enrolled in the study. The incidence of SAP was 21.3%, and the in-hospital mortality rate was 17.0%. Among these indicators, multiple regression analysis revealed that CONUT, PNI, and SIRI were independently associated with SAP. Further ROC curve analysis demonstrated that CONUT (AUC 0.6743, 95% CI 0.6079-0.7408) exhibited the most robust predictive ability for SAP in patients with ICH. Threshold analysis revealed that when CONUT < 6, an increase of 1 point in CONUT was associated with a 1.39 times higher risk of SAP. Similarly, our findings indicate that CONUT has the potential to predict the prognosis of patients with ICH. Among the inflammatory and nutritional markers, CONUT stands out as the most reliable predictor of SAP in patients with ICH. Additionally, it proves to be a valuable indicator for assessing the prognosis of patients with ICH.

Zhao G ，Chen Y ，Gu Y ，Xia X ... -  《Scientific Reports》

Prognostic value of systemic immune-inflammation index, neutrophil-lymphocyte ratio, and thrombocyte-lymphocyte ratio in critically ill patients with moderate to severe traumatic brain injury.

Traumatic brain injury (TBI) is a significant health problem with a high mortality rate. Inflammatory markers can predict the prognosis of TBI where neuroinflammation is essential. In this study, the prognostic value of the systemic immune-inflammation index (SII), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) at admission in patients with critical TBI was investigated. Patients with moderately severe TBI in the intensive care unit (ICU) of a tertiary center between June 2020 and June 2022 were retrospectively reviewed. Patients were classified into survivor and mortality groups. The predictive performance of SII, PLR, and NLR levels calculated from blood results at admission and 28-day mortality and patient outcomes were analyzed. One hundred sixty-one patients were included in this study. The median age of the entire population was 41 (18-90) years, and 80.7% (n = 130) of the patients were male. Falls (42.2%) and traffic accidents (40.4%) were the most common causes of TBI. The most common primary diagnoses in patients with TBI were acute subdural hematoma (30.4%) and subarachnoid hemorrhage (26.1%). The SII and NLR levels were significantly higher in the mortality group, and PLR levels were significantly lower (P = .004, P < .001, P < .001, respectively). In multivariate regression analysis, SII and PLR were independent predictors of mortality (P = .031 and P < .001, respectively). In the receiver operating characteristics (ROC) curve analysis, the cutoff value for SII was ≥ 2951, and the area under the curve (AUC) was 0.662 (95% CI, 0.540-0.784). The cutoff value for NLR was ≥ 9.85, AUC was 0.717 (95% CI, 0.600-0.834), and the cutoff value for PLR was ≤ 130.4, AUC was 0.871 (95% CI, 0.796-0.947). 28-day mortality was 21.1%. Neuroinflammation is essential in patients with critical TBI, and inflammatory markers SII, NLR, and PLR have prognostic importance. SII and PLR are independent predictors of mortality. Early detection of those with a poor prognosis in critically ill TBI patients and planning aggressive treatments may contribute to reducing mortality.

Arslan K ，Sahin AS 《-》

The Trends of Neutrophil-to-Lymphocyte Ratio, Platelet-to-Lymphocyte Ratio, and Systemic Immunoinflammatory Index in Patients with Intracerebral Hemorrhage and Clinical Value in Predicting Pneumonia 30 Days After Surgery.

Zhang J ，Liu C ，Xiao X ，Xie H ，Zhang Y ，Hong Y ，Zhang Y ... -  《-》